The new generation of high efficiency video coding standard (HEVC), although remarkably improves the compression performance, it increases the computational complexity of coding for Screen Content coding (SCC). Theref...
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ISBN:
(数字)9781510622005
ISBN:
(纸本)9781510622005
The new generation of high efficiency video coding standard (HEVC), although remarkably improves the compression performance, it increases the computational complexity of coding for Screen Content coding (SCC). Therefore, how to reduce the coding complexity becomes an important task in HEVC optimization. In this work, the process of quad-tree recursive partitioning has been studied, and the relationship between the coding cost and the mother block and child block has been found in statistics way, and an improved fast early termination coding unit partition based on the cost of the coding unit has been proposed. The experiment results show that the fast algorithm proposed in this paper can save 31.37% of the encoding time at the cost of reduces the coding performance by about 1.02 %.
Random Linear Network coding (RLNC) has emerged as a powerful tool for robust high-throughput multicast. Projection analysis, a recently introduced technique, shows that the distributed packetized RLNC protocol achiev...
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ISBN:
(纸本)9781457705953
Random Linear Network coding (RLNC) has emerged as a powerful tool for robust high-throughput multicast. Projection analysis, a recently introduced technique, shows that the distributed packetized RLNC protocol achieves (order) optimal and perfectly pipelined information dissemination in many settings. In the original approach to RNLC intermediate nodes code together all available information. This requires intermediate nodes to keep considerable data available for coding. Moreover, it results in a coding complexity that grows linearly with the size of this data. While this has been identified as a problem, approaches that combine queuing theory and network coding have heretofore not provided a succinct representation of the memory needs of network coding at intermediates nodes. This paper shows the surprising result that, in all settings with a continuous stream of data, network coding continues to perform optimally even if only one packet per node is kept in active memory and used for computations. This leads to an extremely simple RLNC protocol variant with drastically reduced requirements on computational and memory resources. By extending the projection analysis, we show that in all settings in which the RLNC protocol was proven to be optimal its finite memory variant performs equally well. In the same way as the original projection analysis, our technique applies in a wide variety of network models, including highly dynamic topologies that can change completely at any time in an adversarial fashion.
The H.264/AVC scalable video coding (SVC) includes three kinds of video scalability, namely spatial scalability, temporal scalability, and quality scalability. Two options of quality scalability, CGS and MGS, may be u...
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ISBN:
(纸本)9783642357541
The H.264/AVC scalable video coding (SVC) includes three kinds of video scalability, namely spatial scalability, temporal scalability, and quality scalability. Two options of quality scalability, CGS and MGS, may be used in combinations to achieve various quality layers. Using the CGS alone may incur high encoding complexity. Although the use of MGS may degrade the coding efficiency, it provides higher adaptation flexibility and reduces the coding complexity. In this paper, we investigate the CGS/MGS configurations that lead to good performance. From extensive experiments using the JSVM reference software, we suggest that MGS should be carefully employed. Although MGS always reduces the encoding complexity as compared to using CGS alone, its rate-distortion performance is unstable. Some configurations may cause an unexpected PSNR decrease with an increased bit rate. We investigate the reason and resolve the anomaly by a new CGS/MGS configuration scheme that restricts motion estimation to larger matching blocks.
Hyperspectral (HS) image has rich spectral information content, which facilitates multiple applications including remote sensing. Due to the big data size of the HS image, compression is a required process for the eff...
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ISBN:
(纸本)9781665476478
Hyperspectral (HS) image has rich spectral information content, which facilitates multiple applications including remote sensing. Due to the big data size of the HS image, compression is a required process for the efficiency of image storage and transmission. However, the complexity of the compression algorithms turns real-time compression into a very challenging task. A novel listless set partitioned hyperspectral image compression algorithm is proposed. The proposed compression algorithm uses zero block cube tree structure to exploit the inter and intra sub-band correlation to achieve the compression. From the result, it has been clear that the proposed compression algorithm has low coding complexity with at-par coding efficiency. Thus, it can be a suitable contender for low-resource hyperspectral image sensors.
Wireless sensor network are widely used in various types of environmental monitoring and there are also many applications in the industrial field, we usually deploy sensor nodes in the corresponding areas to monitor a...
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Wireless sensor network are widely used in various types of environmental monitoring and there are also many applications in the industrial field, we usually deploy sensor nodes in the corresponding areas to monitor and collect relevant data, waiting for a sink node to collect the stored data for further analysis and decision. But in some extremely harsh scenarios, the living environment of the sensor node is very bad, hence the data on the nodes will always lose. Generally, we use LT Codes to improve data persistence. However, some difficult problems with regard to the efficiency of coding and decoding of data can not be resolved by traditional solutions. In terms of the above problems, this paper improves the traditional coding method by reducing the number of encoded packets, so that the network congestion can be alleviated under the premise of successful data coding. What's more, we propose an edge layered collection model and a new coding strategy Edge Layering Fountain Codes (ELFC) based on the model, each sensor node inside the network sends its data to the edge nodes which are relatively safe to ensure the secure collection of data and allocate the resource consumption of the sensor nodes around the sink node. On this basis, the Ordered Edge Layering Fountain Codes (OELFC) is further proposed. The OELFC can collect data packets in a low degree-to-high degree manner, which greatly improves the efficiency of data decoding.
Scalable video coding (SVC) encodes image sequences into a single bit stream that can be adapted to various network and terminal capabilities. The H.264/AVC standard includes three kinds of video scalability, spatial ...
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ISBN:
(纸本)9781467302043
Scalable video coding (SVC) encodes image sequences into a single bit stream that can be adapted to various network and terminal capabilities. The H.264/AVC standard includes three kinds of video scalability, spatial scalability, temporal scalability, and quality scalability. Among them, quality scalability refers to image sequences of the same spatio-temporal resolution but with different fidelity levels. Two options of quality scalability are adopted in H.264/AVC, namely CGS (coarse-grain quality scalable coding) and MGS (medium-grain quality scalability), and they may be used in combinations. A refinement layer in CGS is obtained by re-quantizing the (residual) texture signal with a smaller quantization step size (QP). Using the CGS alone, however, may incur notable PSNR penalty and high encoding complexity if numerous rate points are required. MGS partitions the transform coefficients of a CGS layer into several MGS sub-layers and distributes them in different NAL units. The use of MGS may increase the adaptation flexibility, improve the coding efficiency, and reduce the coding complexity. In this paper, we investigate the CGS/MGS configurations that lead to good performance. From extensive experiments using the JSVM (Joint Scalable Video Model), however, we find that MGS should be carefully employed. Although MGS always reduces the encoding complexity as compared to using CGS alone, its rate-distortion is unstable. While MGS typically provides better or comparable rate-distortion performance for the cases with eight rate points or more, some configurations may cause an unexpected PSNR drop with an increased bit rate. This anomaly is currently under investigation.
For high computation complexity of H.264 video coding rate distortion optimization process, this thesis puts forward the adjacent block prediction mode selection algorithm. Using direction gradient to detect texture d...
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For high computation complexity of H.264 video coding rate distortion optimization process, this thesis puts forward the adjacent block prediction mode selection algorithm. Using direction gradient to detect texture direction and edge strength of the current block and its neighborhood, screening out the prediction mode with larger direction gradient prior to the R-D cost calculation, the algorithm can reduce the complexity of the rate distortion optimization. Experimental results indicate that, compared with other algorithms using block texture detection, this algorithm maintains the coding performance and decreases encoding time by 50%.
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